Systems and methods for automatically creating content modification scheme

ABSTRACT

Systems and methods for automatically associating content characteristics to a third-party content are provided. A uniform resource locator identifying a resource is received from a content provider. The content is rendered to produce an object tree. A first node of the object tree is determined, where the first node represents a content slot. A second node of the object tree proximate to the first node is identified. The second node has a content characteristic, which is extracted. The extracted content characteristic is associated with the first node and stored.

RELATED APPLICATIONS

This application is a continuation of, and claims priority to and thebenefit of Patent Application No.: PCT/CN2014/071878, filed Feb. 7,2014, titled “SYSTEMS AND METHODS FOR AUTOMATICALLY CREATING CONTENTMODIFICATION SCHEME” which is hereby incorporated by reference in itsentirety for all purposes.

BACKGROUND

In a computerized content delivery network, first-party contentproviders can provide information for public presentation of resources,such as web pages, documents, applications, and/or other resources.Additional third-party content can also be provided by third-partycontent providers for presentation on the client device together withthe first-party content provided by the first-party content providers.Thus, a user viewing a resource can access the first-party content thatis the subject of the resource as well as the third-party content thatmay or may not be related to the subject matter of the resource.

User experience in viewing the resource is very important for both forfirst-party content providers and third-party content providers. Inorder to improve the user experience, many first-party content providerscontrol the look-and-feel of the third-party content by using closed adservers that provide only advertisements that are specifically designedfor each resource.

SUMMARY

One implementation of the present disclosure is a computerized methodfor automatically creating a content modification scheme for content.The method is performed by a processing circuit. The method includesreceiving a uniform resource locator (URL) from a content provider, theURL identifying a resource. The method further includes rendering theresource to produce an object tree, determining a first node of theobject tree representing a content slot, and identifying a second nodeof the object tree proximate to the first node, the second node having acontent characteristic. The method further includes extracting thecontent characteristic from the second node, associating the contentcharacteristic with the first node of the object tree and storing, in adata structure maintained in a memory element, the association of thedetermined first node and the associated content characteristic.

In some implementations, determining a first node of the object treeincludes traversing the object tree until a first node representing acontent slot is encountered.

In some implementations, determining a first node of the object treecomprises traversing the entire object tree to identify a plurality ofnodes representing a content slot and selecting one of the plurality ofnodes.

In some implementations, identifying a second node comprises identifyinga second node immediately adjacent in the object tree to the first node.

In some implementations, identifying a second node comprises identifyinga plurality of nodes within a predetermined distance from the firstnode.

In some implementations, the method further comprises identifying acontent characteristic associated with at least some of the plurality ofsecond nodes.

In some implementations, identifying a content characteristic comprisesidentifying a content characteristic associated with a majority of theplurality of second nodes.

In some implementations, identifying a content characteristic comprisesaveraging the value of a content characteristic associated with at leastsome of the plurality of second nodes.

In some implementations, identifying a content characteristic comprisesidentifying a font associated with at least one of the plurality ofsecond nodes.

In some implementations, identifying a content characteristic comprisesassigning a weight to each of the plurality of second nodes andidentifying a content characteristic comprising a weighted average ofthe value of a content characteristic associated with at least some ofthe plurality of second nodes.

Another implementation of the present disclosure is a system forautomatically creating a content modification scheme for content. Thesystem includes a receiver accepting a URL from a content provider, theURL identifying a resource, and a renderer in communication with thereceiver, the renderer producing an object tree associated with theresource. The system further includes a first node identifier accessingthe object tree produced by the renderer, the first node identifierdetermining a first node of the object tree representing a content slot,and a second node identifier in communication with the first nodeidentifier, the second node identifier determining a second node of theobject tree proximate to the first node, the second node having acontent characteristic. The system further includes an extractor enginein communication with the second node identifier, the extractor engineextracting content characteristics of the second node, and a linker incommunication with the extractor engine and the first node identifier,the linker associating the content characteristic with the first node ofthe object tree. The system further includes a data manager incommunication with the linker and a memory element, the data managerstoring the association of the determined first node and the associatedcontent characteristic in a data structure maintained in the memoryelement.

In some implementations, the first node identifier comprises a treetraversal module accessing the object tree produced by the renderer, thetree traversal module traversing the object tree until a first noderepresenting a content slot is encountered.

In some implementations, the first node identifier comprises a treetraversal module accessing the object tree produced by the renderer, thetree traversal module traversing the entire object tree to identify aplurality of nodes representing a content slot, and a node selector incommunication with the tree traversal module, the node selectorselecting one of the plurality of nodes to determine a first node.

In some implementations, the second node identifier comprises a closestnode selector in communication with the first node identifier, theclosest node selector identifying the second node immediately adjacentin the object tree to the first node.

In some implementations, the second node identifier comprises a nodedistance calculator in communication with the first node identifier, thenode distance calculator calculating a distance between the first nodeand each of a plurality of second nodes in the object tree, and amulti-node identifier in communication with the renderer, the multi-nodeidentifier identifying the plurality of second nodes within apredetermined distance from the first node.

In some implementations, the multi-node identifier further comprises acontent characteristic analyzer in communication with the node distancecalculator, the content characteristic analyzer identifying a contentcharacteristic associated with at least some of the plurality of secondnodes.

In some implementations, the content characteristic analyzer furthercomprises a node counter accessing the object tree produced by therenderer, the node counter calculating a first number equal to thenumber of nodes in the object tree, and determining a second numberequal to a minimum number of nodes required to be a majority of theplurality of second nodes. The implementation further comprises acontent characteristic analyzer, in communication with the node counter,identifies a content characteristic associated with at least the secondnumber of nodes.

In some implementations, the multi-node identifier further comprisescontent characteristic smoother in communication with the contentcharacteristic analyzer, the content characteristic smoother averagingthe value of a content characteristic associated with at least some ofthe plurality of second nodes.

In some implementations, the multi-node identifier further comprises afont identifier in communication with the content characteristicanalyzer, the font identifier identifying a font associated with atleast one of the plurality of second nodes.

In some implementations, the multi-node identifier further comprisescontent characteristic compounder in communication with the contentcharacteristic analyzer, the content characteristic compounder assigninga weight to each of the plurality of second nodes, and computing aweighted average of the value of a content characteristic associatedwith at least some of the plurality of second nodes.

BRIEF DESCRIPTION OF THE DRAWINGS

Those skilled in the art will appreciate that the summary isillustrative only and is not intended to be in any way limiting. Otheraspects, inventive features, and advantages of the devices and/orprocesses described herein, as defined solely by the claims, will becomeapparent in the detailed description set forth herein and taken inconjunction with the accompanying drawings.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features,aspects, and advantages of the disclosure will become apparent from thedescription, the drawings, and the claims, in which:

FIG. 1 is a block diagram of a computer system including a network,third-party content server, resource server, client devices, contentitem selection system, content item modification system, and datastorage devices, according to a described implementation;

FIG. 2 is a flowchart of one implementation of a process for extractingcontent characteristic for content item modification;

FIG. 3 is a flowchart of one implementation of a process for extractingcontent characteristic for content item modification using content slotdimensions;

FIG. 4 is a block diagram illustrating one implementations of thecontent item modification system of FIG. 1 in greater detail, showing areceiver, a renderer module, a first node identifier module, a secondnode identifier module, an extractor engine module, a linker module, adata manager module, and a node dimensions module; and

FIG. 5 is a block diagram of one implementations of an object tree.

It will be recognized that some or all of the figures are schematicrepresentations for purposes of illustration. The figures are providedfor the purpose of illustrating one or more implementations with theexplicit understanding that they will not be used to limit the scope orthe meaning of the claims.

DETAILED DESCRIPTION

Following below are more detailed descriptions of various conceptsrelated to, and implementations of, methods, apparatuses, and systemsfor providing information on a computer network. The various conceptsintroduced above and discussed in greater detail below may beimplemented in any of numerous ways, as the described concepts are notlimited to any particular manner of implementation. Specificimplementations and applications are provided primarily for illustrativepurposes.

Referring generally to the FIGURES, systems and methods for extractingand generating content modification are shown, according to a describedimplementation. The systems and methods described herein may be used toautomatically create a content modification scheme and to use thecontent modification scheme to modify a third-party content item that istailored to a particular resource such as a web page. In operation, acontent item modification system in accordance with the presentdisclosure receives a uniform resource locator (URL) from a content itemselection system. The URL identifies the particular resource. Thecontent item modification system uses the URL to navigate to and renderthe resource. A first content slot on the resource to which athird-party content item will be displayed is determined. A secondcontent slot on the resource is identified, where the second contentslot has a content characteristic. Content characteristic includescolors, color schemes, fonts, styles, and dimensions. Contentcharacteristic may also specify that no animations, sounds, or videosshould be played. Content characteristics are extracted from the secondcontent slot. The extracted content characteristics are stored inassociation with the first content slot. The content item modificationsystem may then use the stored content characteristics to modifythird-party content item that will be provided in the first contentslot.

A client device may request a first-party content from a first-partycontent provider. The first-party content may be a web page requested bythe client device or a stand-alone application (e.g., a video game, achat program, etc.) running on the client device. The first-partycontent can include text, image, animation, video, and/or audioinformation. The first-party content provider can provide first-partycontent via a resource server for presentation on a client device overthe Internet. Additional third-party content can also be provided bythird-party content providers for presentation on the client devicetogether with the first-party content provided by the first-partycontent providers. The third-party content may be an advertisement thatappears in conjunction with a requested resource, such as a web page(e.g., a search result web page from a search engine, a web page thatincludes an online article, a web page of a social networking service,etc.) or with an application (e.g., an advertisement within a game).Thus, a user viewing a resource can access the first-party content thatis the subject of the resource as well as the third-party content thatmay or may not be related to the subject matter of the resource.

The first-party content provider may request a third-party contentserver for a third-party content. The first-party content provider mayalso provide a resource or content to the client device that requiresthe client device to request additional third-party content fromthird-party content server. A third-party content server may have aplurality of third-party content items that are from, for instance,different third-party content providers such as advertisers. Athird-party content server, when providing third-party content items forpresentation with requested resources via the Internet or other network,may utilize a content item selection system to control or otherwiseinfluence the selection and serving of the third-party content items. Insome implementations, the first-party content provider, web page serverand/or the client device can communicate with plurality of third-partycontent servers and content item selection systems. For instance, theweb page server may alternate between two third-party content servers oruse a third-party content server for specific content slots of a webpage.

A third-party content provider may specify selection criteria (such askeywords) and corresponding bid values that are used in the selection ofthe third-party content items. The bid values may be utilized by thecontent item selection system in an auction to select and serve contentitems for presentation with a resource. For instance, a third-partycontent provider may place a bid in the auction that corresponds to anagreement to pay a certain amount of money if a user interacts with theprovider's content item (e.g., the provider agrees to pay $3 if a userclicks on the provider's content item). In some instances, the contentitem selection system uses content item interaction data to determinethe performance of the third-party content provider's content items thatare modified by content characteristics extracted from the web page orfrom other third-party content presented on the web page. For instance,users may be more inclined to click on third-party content items thatare modified by extracted content characteristics than unmodifiedthird-party content items. Accordingly, auction bids to place thethird-party content items may be higher or lower for web page publishersor first-party content providers that have an agreement with thethird-party content providers to modify content characteristics of thethird-party content items such as advertisements.

In some instances, one or more performance metrics for the third-partycontent items may be determined and indications of such performancemetrics may be provided to the third-party content provider via a userinterface for the content item management account. For instance, theperformance metrics may include a cost per impression (CPI) or cost perthousand impressions (CPM), where an impression may be counted, forinstance, whenever a content item is selected to be served forpresentation with a resource. In some instances, the performance metricmay include a click-through rate (CTR), defined as the number of clickson the content item divided by the number of impressions. In someinstances, the performance metrics may include a cost per engagement(CPE), where an engagement may be counted when a user interacts with thecontent item in a specified way. An engagement can be sharing a link tothe content item on a social networking site, submitting an emailaddress, taking a survey, and watching a video to completion. Stillother performance metrics, such as cost per action (CPA) (where anaction may be clicking on the content item or a link therein, a purchaseof a product, a referral of the content item, etc.), conversion rate(CVR), cost per click-through (CPC) (counted when a content item isclicked), cost per sale (CPS), cost per lead (CPL), effective CPM(eCPM), and/or other performance metrics may be used. The variousperformance metrics may be measured before, during, or after contentselection, content presentation, user click, or user engagement. In oneinstance, user click and user engagement may be measured by a clickserver that may be part of the content item management service.

In some instances, a web page or other resource (such as, for instance,an application) includes one or more content item slots in which aselected and served third-party content item may be displayed. The code(e.g., JavaScript®, HTML, etc.) defining a content item slot for a webpage or other resource may include instructions to request a third-partycontent item from the content item selection system to be presented withthe web page. In some implementations, the code may include an imagerequest having a content item request URL that may include one or moreparameters (e.g., /page/contentitem?devid=abc123&devnfo=A34r0). Suchparameters may, in some implementations, be encoded strings such as“devid=abc123” and/or “devnfo=A34r0.”

The selection of a third-party content item to be served with theresource by a content item selection system may be based on severalinfluencing factors, such as a predicted click through rate (pCTR), apredicted conversion rate (pCVR), and a bid associated with the contentitem, etc. Such influencing factors may be used to generate a value,such as a score, against which other scores for other content items maybe compared by the content item selection system through an auction. ThepCTR and the pCVR may be higher for third-party content items thatmatching content characteristics as another third-party content item inthe same web page or a content. Users viewing the web page may, forinstance, have better user experience if the third-party content itemcontains matching content characteristics. Users may in turn be moreinclined to click on the third-party content.

FIG. 1 is a block diagram of an implementation of a system 100 forcontent item modification using at least one computer network such asthe network 101. The network 101 may include a local area network (LAN),wide area network (WAN), a telephone network, such as the PublicSwitched Telephone Network (PSTN), a wireless link, an intranet, theInternet, or combinations thereof. The system 100 can also include atleast one data processing system, such as a content item selectionsystem 108. The content item selection system 108 can include at leastone logic device, such as a computing device having a data processor, tocommunicate via the network 101, for instance with a third-party contentserver 102, a resource server 104, a user device 106, content itemmodification system 110, a resource renderer 111, and/or a data storagedevice 112. In some implementations, the content selection system 108may include a content item modification system 110. The content itemselection system 108 may also include an interface configured to receivedata via the network 101 and to provide data from the content itemselection system 108 to any of the other devices on the network 101. Thecontent item selection system 108 can include a server, such as anadvertisement server or otherwise. Resource renderer 110 may receiveresources from resource servers 104 via network 101 and render such dataas a snapshot image (e.g., a visual representation of resources 106)and/or as a document object model (DOM) tree. The rendered data may betransmitted from resource renderer 111 to content item modificationsystem 110 via network 101.

Still referring to FIG. 1, computer system 100 is shown to include acontent item modification system 110. The content item modificationsystem 110 can include at least one logic device, such as a computingdevice having a data processor, to communicate via the network 101, forinstance with a third-party content server 102, a resource server 104, auser device 106, content item selection system 108, and/or a datastorage device 112. The content item modification system 110 can includeone or more data processors, such as a content placement processor,configured to execute instructions stored in a memory device to performone or more operations described herein. In other words, the one or moredata processors and the memory device of the content item modificationsystem 110 may form a processing module. For instance, a contentmodification system module may be part of a content item selectionsystem 108. The processor may include a microprocessor, anapplication-specific integrated circuit (ASIC), a field-programmablegate array (FPGA), etc., or combinations thereof. The memory mayinclude, but is not limited to, electronic, optical, magnetic, or anyother storage or transmission device capable of providing processor withprogram instructions. The memory may include a floppy disk, compact discread-only memory (CD-ROM), digital versatile disc (DVD), magnetic disk,memory chip, read-only memory (ROM), random-access memory (RAM),Electrically Erasable Programmable Read-Only Memory (EEPROM), erasableprogrammable read only memory (EPROM), flash memory, optical media, orany other suitable memory from which processor can read instructions.The instructions may include code from any suitable computer programminglanguage such as, but not limited to, C, C++, C#, Java®, JavaScript®,Perl®, HTML, XML, Python®, and Visual Basic®. The processor may processinstructions and output data to effect modification of a third-partycontent that is selected by a content item selection system 108 based ona web page or content provided by a resource server 104 or a third-partycontent server 102. Content item modification system 110 may beconfigured to extract content characteristic (e.g., colors, colorschemes, fonts, styles, content characteristic specifying that noanimations should be played, dimensions, etc.) from content itemsassociated with resources. In addition to the processing circuit, thecontent item modification system 110 may include one or more databasesconfigured to store data. A data storage device 112 may be connected tothe content item modification system 110 through the network 101.Content item modification system 110 is described in greater detail withreference to FIG. 4.

Client devices 106 may include any number and/or type of user-operableelectronic devices. For instance, client devices 106 may include adesktop computer, laptop, smart phone, wearable device, smart watch,tablet, personal digital assistant, set-top box for a television set,smart television, gaming console device, mobile communication devices,remote workstations, client terminals, entertainment consoles, or anyother devices configured to communicate with other devices via thenetwork 101. User devices 106 may be capable of receiving resourcecontent from resources and/or third-party content items from contentselection system 108 and/or content modification system 110. The devicemay be any form of electronic device that includes a data processor anda memory. The memory may store machine instructions that, when executedby a processor, cause the processor to perform one or more of theoperations described herein. The memory may also store data to effectpresentation of one or more resources, content items, etc. on thecomputing device. The processor may include a microprocessor, anapplication-specific integrated circuit (ASIC), a field-programmablegate array (FPGA), etc., or combinations thereof. The memory mayinclude, but is not limited to, electronic, optical, magnetic, or anyother storage or transmission device capable of providing processor withprogram instructions. The memory may include a floppy disk, compact discread-only memory (CD-ROM), digital versatile disc (DVD), magnetic disk,memory chip, read-only memory (ROM), random-access memory (RAM),Electrically Erasable Programmable Read-Only Memory (EEPROM), erasableprogrammable read only memory (EPROM), flash memory, optical media, orany other suitable memory from which processor can read instructions.The instructions may include code from any suitable computer programminglanguage such as, but not limited to, ActionScript®, C, C++, C#, HTML,Java®, JavaScript®, Perl®, Python®, Visual Basic®, and XML.

The user device 106 can execute a software application (e.g., a webbrowser or other application) to retrieve content from other computingdevices over network 101. Such an application may be configured toretrieve first-party content from a resource server 104. In some cases,an application running on the user device 106 may itself be first-partycontent (e.g., a game, a media player, etc.). User devices 106 mayinclude a user interface element (e.g., an electronic display, aspeaker, a keyboard, a mouse, a microphone, a printer, etc.) forpresenting content to a user, receiving user input, or facilitating userinteraction with electronic content (e.g., clicking on a content item,hovering over a content item, etc.). User devices 106 may function as auser agent for allowing a user to view HTML encoded content. In someimplementations, user devices 106 include an application (e.g., a webbrowser, a resource renderer, etc.) for converting electronic contentinto a user-comprehensible format (e.g., visual, aural, graphical,etc.). For instance, the user device 106 may execute a web browserapplication which provides a browser window on a display of the clientdevice. The web browser application that provides the browser window mayoperate by receiving input of a uniform resource locator (URL), such asa web address, from an input device (e.g., a pointing device, akeyboard, a touch screen, or another form of input device). In response,one or more processors of the client device executing the instructionsfrom the web browser application may request data from another deviceconnected to the network 101 referred to by the URL address (e.g., aresource server 104). The other device may then provide web page dataand/or other data to the user device 106, which causes visual indicia tobe displayed by the display of the user device 106. Accordingly, thebrowser window displays the retrieved first-party content, such as webpages from various websites, to facilitate user interaction with thefirst-party content. User devices 106 may include a processor capable ofprocessing embedded information (e.g., meta information embedded inhyperlinks, etc.) and executing embedded instructions. Embeddedinstructions may include computer-readable instructions (e.g., softwarecode, JavaScript®, ECMAScript®, etc.) associated with a content slotwithin which a third-party content item is presented.

In some implementations, user devices 106 are capable of detecting aninteraction with a distributed content item. An interaction with acontent item may include displaying the content item, hovering over thecontent item, clicking on the content item, viewing source informationfor the content item, or any other type of interaction between userdevices 106 and a content item. Interaction with a content item does notrequire explicit action by a user with respect to a particular contentitem. In some implementations, an impression (e.g., displaying orpresenting the content item) may qualify as an interaction. The criteriafor defining which user actions (e.g., active or passive) qualify as aninteraction may be determined on an individual basis (e.g., for eachcontent item) by content item selection system 108 or by content itemmodification system 110.

User devices 106 may generate a variety of user actions. For instance,user devices 106 may generate a user action in response to a detectedinteraction with a content item. The user action may include a pluralityof attributes including a content identifier (e.g., a content ID orsignature element), a device identifier, a referring URL identifier, atimestamp, or any other attributes describing the interaction. Userdevices 106 may generate user actions when particular actions areperformed by a user device (e.g., resource views, online purchases,search queries submitted, etc.). The user actions generated by userdevices 106 may be communicated to content item modification system 110or a separate accounting system.

For situations in which the systems discussed here collect personalinformation about users, or may make use of personal information, theusers may be provided with an opportunity to control whether programs orfeatures collect user information (e.g., information about a user'ssocial network, social actions or activities, profession, a user'spreferences, or a user's current location), or to control whether and/orhow to receive content from the content server that may be more relevantto the user. In addition, certain data may be treated (e.g., by contentitem selection system 108) in one or more ways before it is stored orused, so that personally identifiable information is removed. Forinstance, a user's identity may be treated so that no personallyidentifiable information can be determined for the user, or a user'sgeographic location may be generalized where location information isobtained (such as to a city, ZIP code, or state level), so that aparticular location of a user cannot be determined. Thus, a user mayhave control over how information is collected (e.g., by an application,by user devices 106, etc.) and used by content item selection system108.

The resource server 104 can include a computing device, such as aserver, configured to host a resource, such as a web page or otherresource (e.g., articles, comment threads, music, video, graphics,search results, information feeds, etc.). The resource server 104 may bea computer server (e.g., a file transfer protocol (FTP) server, filesharing server, web server, etc.) or a combination of servers (e.g., adata center, a cloud computing platform, etc.). The resource server 104can provide resource data or other content (e.g., text documents, PDFfiles, and other forms of electronic documents) to the user device 106.In one implementation, the user device 106 can access the resourceserver 104 via the network 101 to request data to effect presentation ofa resource of the resource server 104.

Resources provided by the resource server 104 may include any type ofinformation or data structure that can be provided over network 101. Insome implementations, resources may be identified by a resource addressassociated with the resource server 104 (e.g., a URL). Resources mayinclude web pages (e.g., HTML web pages, PHP web pages, etc.), wordprocessing documents, portable document format (PDF) documents, images,video, programming elements, interactive content, streaming video/audiosources, or other types of electronic information. Resources provided bythe resource server 104 may be web pages, local resources, intranetresources, Internet resources, or other network resources. In someimplementations, resources include one or more web pages to which userdevices 106 are directed (e.g., via an embedded hyperlink) when userdevices 106 interact with a third-party content item modified by acontent item modification system 110 and provided by a content itemselection system 108.

One or more third-party content providers may have third-party contentservers 102 to directly or indirectly provide data for third-partycontent items to the content item selection system 108, the content itemmodification system 110, and/or to other computing devices via network101. The content items may be in any format that may be presented on adisplay of a user device 106, for instance, graphical, text, image,audio, video, etc. The content items may also be a combination (hybrid)of the formats. The content items may be banner content items,interstitial content items, pop-up content items, rich media contentitems, hybrid content items, Flash® content items, cross-domain iframecontent items, etc. The content items may also include embeddedinformation such as hyperlinks, metadata, links, machine-executableinstructions, annotations, etc. In some instances, the third-partycontent servers 102 may be integrated into the content item selectionsystem 108 and/or the data for the third-party content items may bestored in a database of the content item selection system 108.

In one implementation, a content item selection system 108 can receive,via the network 101, a request for a content item to present with aresource. The received request may be received from a resource server104, a user device 106, and/or any other computing device. The resourceserver 104 may be owned or ran by a first-party content provider thatmay include instructions for a plurality of content item selectionsystems 108 to provide third-party content items with one or moreresources of the first-party content provider on the resource server104. In one implementation, the resource may include a web page. Theuser device 106 may be a computing device operated by a user(represented by a device identifier), which, when accessing a resourceof the resource server 104, can make a request to a content itemselection system 108 for content items to be presented with theresource, for instance. The content item request can include requestingdevice information (e.g., a web browser type, an operating system type,one or more previous resource requests from the requesting device, oneor more previous content items received by the requesting device, alanguage setting for the requesting device, a geographical location ofthe requesting device, a time of a day at the requesting device, a dayof a week at the requesting device, a day of a month at the requestingdevice, a day of a year at the requesting device, etc.) and resourceinformation (e.g., URL of the requested resource, one or more keywordsof the content of the requested resource, text of the content of theresource, a title of the resource, a category of the resource, a type ofthe resource, etc.). The information that the content item selectionsystem 108 receives can include a HyperText Transfer Protocol (HTTP)cookie which contains a device identifier (e.g., a random number) thatrepresents the user device 106. In some implementations, the deviceinformation and/or the resource information may be appended to a contentitem request URL (e.g.,contentitem.item/page/contentitem?devid=abc123&devnfo=A34r0). In someimplementations, the device information and/or the resource informationmay be encoded prior to being appended the content item request URL. Therequesting device information and/or the resource information may beutilized by the content item selection system 108 to select third-partycontent items to be served with the requested resource and presented ona display of a user device 106.

In one implementation, the content item selection system 108 sends theURL of the resource to a content item modification system 110, whichextracts content characteristic of a third-party content item in theresource. The third-party content item may be provided by a content itemselection system 108. The extracted content characteristic may be storedin a data storage device 112, resource server 104, and/or the contentitem selection system 108, in association with the web page or theresource.

In some implementations, the third-party content provider may manage theselection and serving of content items by content item selection system108. For instance, the third-party content provider may set bid valuesand/or selection criteria via a user interface that may include one ormore content item conditions or constraints regarding the serving ofcontent items. A third-party content provider may specify that a contentitem and/or a set of content items should be selected and served foruser devices 110 having device identifiers associated with a certaingeographic location or region, a certain language, a certain operatingsystem, a certain web browser, etc. In another implementation, thethird-party content provider may specify that a content item or set ofcontent items should be selected and served when the resource, such as aweb page, document, etc., contains content that matches or is related tocertain keywords, phrases, etc. The third-party content provider may seta single bid value for several content items, set bid values for subsetsof content items, and/or set bid values for each content item. Thethird-party content provider may also set the types of bid values, suchas bids based on whether a user clicks on the third-party content item,whether a user performs a specific action based on the presentation ofthe third-party content item, whether the third-party content item isselected and served, and/or other types of bids.

Still referring to FIG. 1, system 100 is shown to include a resourcerenderer 111. Resource renderer 111 may be a hardware or softwarecomponent capable of interpreting resources from resource servers 104and creating a visual representation (e.g., an image, a display, etc.)thereof. For instance, resources may include marked up content (e.g.,HTML, XML, image URLs, etc.) as well as formatting information (e.g.,CSS, XSL, etc.). Resource renderer 111 may download the marked upcontent and formatting information and render resources according toWorld Wide Web Consortium (W3C) standards. Resource renderer 111 maycreate a “snapshot image” of resources and/or construct a documentobject model (DOM) tree representing resources.

The snapshot image may be a visual representation of a particularresource. The snapshot image may illustrate the visual appearance of theresource as presented on a user interface device (e.g., an electronicdisplay screen, a computer monitor, a touch-sensitive display, etc.)after rendering resource. The snapshot image may include colorinformation (e.g., pixel color, brightness, saturation, etc.) and styleinformation (e.g., square corners, rounded edges, modern, rustic, etc.)for resource. In some implementations, the snapshot image may be apicture file having any viable file extension (e.g. jpg, .png, .bmp,etc.).

The DOM tree may be a hierarchical model of a particular resource. TheDOM tree may include image information (e.g., image URLs, displaypositions, display sizes, alt text, etc.), font information (e.g., fontnames, sizes, effects, etc.), color information (e.g., RGB color values,hexadecimal color codes, etc.) and text information for the resource.

In various implementations, resource renderer 111 may be part of contentitem modification system 110 or a separate component. Resource renderer111 may prepare the snapshot image and/or DOM tree in response to arendering request from content item modification system 110. Resourcerenderer 111 may transmit the snapshot image and/or DOM tree to contentitem modification system 110 in response to the rendering request.

Still referring to FIG. 1, computer system 100 is shown to include datastorage devices 112. Data storage devices 112 may be any type of memorydevice capable of storing content characteristic, profile data, contentitem data, accounting data, or any other type of data used by contentitem modification system 110 or another component of computer system100. Data storage devices 112 may include any type of non-volatilememory, media, or memory devices. For instance, data storage devices 112may include semiconductor memory devices (e.g., EPROM, EEPROM, flashmemory devices, etc.) magnetic disks (e.g., internal hard disks,removable disks, etc.), magneto-optical disks, and/or CD ROM and DVD-ROMdisks.

In some implementations, data storage devices 112 are local to contentitem modification system 110, content item selection system 108,resource server 104, or third-party content server 102. In otherimplementations, data storage devices 112 are remote data storagedevices connected with content item modification system 110 and/orcontent item selection system 108 via network 101. In someimplementations, data storage devices 112 are part of a data storageserver or system capable of receiving and responding to queries fromcontent item modification system 110 and/or content item selectionsystem 108. In some implementations, data storage devices 112 areconfigured to store extracted content characteristics. For instance,data storage devices 112 may store content characteristics data forvarious content items displayed on resource.

FIG. 2 is a flowchart of one implementation of a process for extractingcontent characteristic for content item modification. In brief overview,the method generally includes receiving a URL (step 210), rendering theresource to produce an object tree (step 220), determining a first nodeof the object tree representing a content slot (step 230), andidentifying a second node of the object tree proximate to the first node(step 240). The method further includes extracting a contentcharacteristic from the second node (step 250), associating the contentcharacteristic with the first node of the object tree (step 260), andstoring in a data structure maintained in a memory element, theassociation of the determined first node and the associated contentcharacteristic (step 270). In other implementations, these steps can beperformed in a different order.

Specifically, the method includes receiving a URL from a contentprovider, the URL identifying a resource (step 210). The URL may bereceived from a content item selection system 108, as a part of arequest to modify a third-party content item. The URL may also bereceived from a third-party content server 102 that is using the contentitem modification system 110 after a content item has been selected. TheURL may also be received from the resource server 104 as part of arequest to modify all or some of the third-party content items on theresource. In some implementations, instead of receiving the URL, a webcrawler or a bot may crawl to a web page to find the URL. For instance,a web crawler may crawl to a web page that URL links to a plurality ofother web pages. The web crawler may find one of the URL links. The URLmay specify the location of a resource on the resource server 104 towhich the resource renderer 111 or a user device may navigate. Theresource may be a webpage, a local resource, an intranet resource, anInternet resource, or other network resource. The resource may containmultiple content slots to which third-party content items may beprovided.

As shown in FIG. 2, the method further includes rendering the resourceto produce an object tree (step 220). The resource renderer 111 or therenderer module 410 may render the resource. The object tree may be aDOM tree. In some implementations, rendering the resource includesparsing the web page corresponding to the received resource. Forinstance, the web page may be a HTML file that is then parsed to producea corresponding DOM tree. In some implementations, parsing the resourcemay be done without rendering the web page. For instance, parser may bea module used by the resource renderer such that the parser module maybe used without rendering the web page. In some implementations,rendering the resource may create a snapshot image. For instance, thesnapshot image may be a visual representation of the resource. Thesnapshot image may illustrate the visual appearance of the resource aspresented on a user interface device after rendering the resource. Thesnapshot image may include content items in content slots, the contentitems having content characteristics including color, color scheme,style, font, content characteristic that specifies no animation shouldbe played, etc. The snapshot image may be associated with the DOM tree.

As shown in FIG. 2, the method further includes determining a first nodeof the object tree representing a content slot (step 230). The objecttree may be parsed to determine a first content slot. The content slotsmay be identified by examining each node of the object tree andsearching for a particular word such as, for instance, “adsbygoogle.”The content slots may also be determined by looking for specific HTMLtags associated with the nodes such as the tag “<script>.” In someimplementations, the object tree is traversed until a first noderepresenting a content slot is encountered. For instance, the objecttree is traversed from the beginning, and each node is examined todetermine whether it is a content slot. In some implementations, thefirst node may be selected among a plurality of content slots becausethe first node has fewer content characteristics. For instance, theentire object tree is traversed to identity all or some content slots.One of the plurality of content slots is chosen as a first node basedon, for instance, whether a content slot has or does not have certaincontent characteristics. The selected content slot, for instance, maynot specify font while other content slots may specify font. In someimplementations, one of the plurality of content slots may be chosenbased on total number of content characteristics it lacks or has. Forinstance, the content slot may be chosen because it does not have anycontent characteristic.

As shown in FIG. 2, the method further includes identifying a secondnode of the object tree proximate to the first node, the second nodehaving a content characteristic (step 240). The second node may have oneor more content characteristic that is absent or is different from thefirst node. For instance, the first node may lack a contentcharacteristic specifying font information and the second node may havea content characteristic specifying font. In general, a content slot mayspecify a color, a color scheme, a font, styles, dimensions, contentcharacteristic specifying that no animations, sounds, or videos shouldbe played, or other content characteristics. In some implementations, acontent slot that is closest to the first node is identified as thesecond node. The distance may be calculated by using the object tree todetermine the number of connections or links between two nodes in theobject tree. The number of connections or links can be measured usingthe object tree. If, for instance, a parent node contains two childrennodes, where each child node is a content slot, then the number of linksbetween the two children nodes is two. In some implementations, afterthe whole object tree is parsed and every content slot is found,distance between the first node and some or all other content slots iscalculated. The node with the smallest distance from the first node isselected as the second node. For instance, the second node of the objecttree may be identified in the object tree by traversing the tree afterthe first node and identifying a first content slot. For anotherinstance, the object tree is traversed after the first node, and thefirst content slot encountered is selected as the second node. Foranother instance, the object tree is traversed backwards from the firstnode to find the second node. In yet another instance, the object treeis traversed backwards and forwards to find the closest content slotproximate to the first node. In some implementations, spatial distanceis calculated to determine the distance between two nodes. The snapshotimage produced by the resource renderer 111 may be used to calculate thedistance in pixels between two content slots, each corresponding to anode in the object tree. For instance, spatial distance between twocontent slots corresponding to two nodes of a webpage may be calculated.A content slot that is closest to the first node in terms of spatialdistance may be selected as the second node.

In some implementations, a plurality of second nodes may be identified.In some implementations, the plurality of second nodes may include allnodes in the object tree corresponding to a content slot. In someimplementations, at least some of the plurality of second nodes may havea content characteristic that is different from or absent in the firstnode. In some implementations, a plurality of second nodes may beselected based on having a content characteristic not specified in ordifferent from the content characteristic of the first node. Forinstance, the first node may not have a content characteristicspecifying color. The content slots for plurality of second nodes may beselected at least partially based on whether the content slot containscontent characteristic specifying color. In some instance, the pluralityof second nodes may only include nodes within a predetermined distancefrom the first node. The predetermined distance may be specified by aresource server 104 or a third-party content server 102. The contentitem modification system 110 or the content item selection system 108may provide a default value for the predetermined distance. The distancebetween the first node and each node corresponding to a content slot canbe measured and the nodes that are closer than the predetermineddistance from the first node can be selected. For another instance, apredetermined spatial distance may be used to select a plurality ofsecond nodes that are within that spatial distance. If, for instance,the predetermined spatial distance is 50 pixels, any nodes withcorresponding content slots within 50 pixels of the content slotcorresponding to the first node may be selected as a part of pluralityof second nodes. In some implementations, a predetermined number ofcontent slots that are closest to the content slot corresponding to thefirst node may be selected. For instance, five closest content slots maybe selected. In some implementations, snapshot image is used tospatially group the content slots using cluster analysis such as k-meansclustering. Every content slot in the same cluster as the first node maybe selected as part of the plurality of second nodes.

In some implementations, the identified plurality of second nodes may beselected based on having a repeated pattern. For instance, all thecontent slots on the resource may be collected. A content characteristicthat is most prevalent among all content slots in the resource may beidentified. Each content slots specifying that prevalent contentcharacteristic may be selected as part of the plurality of second nodes.For instance, if there are ten content slots in the resource and nine ofthem specify a specific font, those nine content slots may be selectedas the plurality of second nodes. In some implementations, to determinethe prevalent content characteristic of the content slots, similarcontent characteristic values may be grouped together. For instance, forcolors, content slots that have similar color may be grouped together todetermine whether the color is repeated. For this instance, a color maybe similar if they are close in Red-Green-Blue (RGB) space, in aperception-based color space, or in any other color space. In someimplementations, content slots may have more than one contentcharacteristics that are repeated. For instance, ten content slots maybe part of the plurality of second nodes. Nine of the content slots mayhave the same font, while eight of the content slots may have the samecolor. Content slots that have the same font and the content slots thathave the same color may all be selected as part of the plurality ofsecond nodes.

For implementations that identify a plurality of second nodes, themethod 200 may further include identifying a content characteristicassociated with at least some of the plurality of second nodes 442. Forinstance, the plurality of second nodes may include two content slotsand one of the content slot may specify a color blue. The contentcharacteristic of color blue may be identified. In some implementations,a repeating content characteristic among the plurality of second nodesmay be identified. A content characteristic may be associated with amajority or a subset of the plurality of second nodes. For instance,referring briefly to FIG. 5, there may be three content slots identifiedas part of the plurality of second nodes. Two of the content slots,nodes 510 and 520, may specify that animations are turned off, while theother content slot 530 may specify that animations are turned on. Thecontent characteristic of animation turned off is selected because it isshared by the majority of the content slots. Alternatively, the contentcharacteristic of color blue is selected because it is repeated. In someimplementations, multiple content characteristics may be identified,where each content characteristic is associated with a majority or asubset of the plurality of second nodes. For instance, there may be tencontent slots identified as plurality of the second nodes. Nine of thenodes may specify content characteristic of color blue, and eight of thenodes may specify a specific font. Both the color blue and the specificfont are shared in majority of the plurality of second nodes, and thusboth content characteristics are identified.

For implementations that identify a plurality of second nodes, themethod 200 may optionally include averaging the content characteristicvalues of at least some the content slots identified as part of theplurality of second nodes. For instance, referring briefly to FIG. 5,the content slots of the plurality of second nodes may specify a colorthat is similar to blue but are not exactly the same as the colorspecified by all or some of the other content slots. There may be threecontent slots identified as the plurality of second nodes. One contentslot 510 may have, for instance, a RGB hexadecimal value of #0000FF,another content slot 520 may have a RGB hexadecimal value of #0000EE,and yet another content slot 530 may have a RGB hexadecimal value of#0000CD. The average value of the three RGB hexadecimal value iscalculated as #0000E9. In some implementations, a subset of contentslots from the plurality of second nodes may be identified as sharingsimilar content characteristics that may be averaged. For instance,there may be four content slots in the plurality of second nodes. Threeof the content slots may specify similar colors such as RGB hexadecimalvalues #0000FF, #0000EE, and #0000CD. The fourth content slot mayspecify a different RGB hexadecimal value, such as #FF0000. The firstthree content slots with similar color may be averaged while the fourthcontent slot is not taken as part of the average. The subset of contentslots may be determined by cluster analysis such as k-means clusteringanalysis.

For some implementations that identify a plurality of second nodes, themethod 200 in FIG. 2 may optionally include calculating a weightedaverage by assigning a weight to each of the plurality of second nodesand identifying a content characteristic comprising a weighted averageof the value of a content characteristic associated with at least someof the plurality of second nodes. The weights may sum up to 1 andindividually be greater than 0 and less than 1. In some implementations,the weight may be determined by the distance to the first node, by thesize of the content slot, or by the salience score of the content slotin the snapshot image of the resource. For instance, referring brieflyto FIG. 5, there may be three content slots in the plurality of secondnodes. The first node may be on the top of the resource. One contentslot 510 may be adjacent to the first node, another content slot 520 maybe in the middle of the resource, and yet another content slot 530 maybe at the bottom of the resource. The content slot 510 next to the firstnode may have the highest weight, and the content slot at the bottom 530may have the lowest weight. The content slot 510 next to the first nodehave a color of hexadecimal value #0000FF and a weight of 0.6. Thecontent slot 520 in the middle of the resource may have a color ofhexadecimal value #0000EE and a weight of 0.3. The content slot 530 atthe bottom of the resource may have a color of hexadecimal value #0000CDand a weight of 0.1 The weighted average will be a hexadecimal value of#0000F5. In some implementations, weights may be determined by relativesize of each content slots, and the area of the content slots may beused to calculate the relative weight assigned to each content slot. Forinstance, bigger content slots may be given a bigger weight as comparedto the smaller content slots. The area of a content slot may becalculated by its dimensions or by the snapshot image produced by theresource renderer 111.

In some implementations, a salience score of a content slot may becalculated to assign weights. A salience score for a content slot mayindicate the relative importance or prominence with which the contentslot is displayed on the resource. After all salience scores has beencalculated for each of the plurality of second nodes, the saliencescores may be normalized so as to sum up to 1. The salience score maydepend on, for instance, a vertical placement of the image (e.g., top ofthe page, middle of the page, bottom of the page, etc.), the displaysize of the image (e.g., display height, display width, etc.), whetherthe image is centered on the resource, and/or other image saliencescoring criteria.

One instance of a content slot salience scoring algorithm that can beused to assign a salience score is:

Salience=α*sigmoid₁(position_(y) ,y ₀ ,dy)+β*sigmoid₂(width,w ₀ ,d_(size))*sigmoid₂(height,h ₀ ,d _(size))+δ*central_alignment

In some implementations, α, β, and δ are all positive and sum to 1.0.

-   Sigmoid₁ (position_(y), y₀, dy) may be a sigmoid function ranging    from 1.0 at position_(y)=0 (e.g., the top of resource) to 0.0 at    position₁=00 (e.g., the bottom of the resource, significantly    distant from the top of the resource, etc.). y₀ may be the point at    which Sigmoid₁=0.5 and dy may control the slope of the sigmoid    function around y₀. Sigmoid₂ may be defined as (1−Sigmoid₁) and    central_alignment may be a measure of whether the image is centrally    aligned (e.g., horizontally centered) on the resource.    Central_alignment may be 1.0 if the image is perfectly centered and    may decrease based on the distance between the center of the image    and the horizontal center of the resource.

For some content characteristics, average value or weight average valuecannot or should not be computed. For instance, categorical or ordinalvariables such as font cannot be averaged. For another instance,dimensions of content slots should not be averaged because thedimensions should match that of the third-party content item. For yetanother instance, one content characteristic specifies that animations,sounds, or videos should be turned off in the third-party content item,and such content characteristic should not be averaged.

As shown in FIG. 2, the method further includes extracting a contentcharacteristic from the second node. In some implementations, the secondnode may have only one content characteristic. In some implementations,the second node may have more than one content characteristics. Thecontent characteristics may be extracted from the object tree or theresource. In some implementations, the content characteristics may beextracted from a snapshot image of the resource that is rendered by theresource renderer 111. For instance, portions of the snapshot imagecorresponding to the second node may be examined to extract differentcontent characteristics. In some implementations, only portions of theresource that correspond to the second node may be rendered. Differentcontent characteristics may be extracted from the rendered image. Forinstance, color of the content item in the second node may be extracted.Extracting from the rendered snapshot image allows extraction ofadditional content characteristic that may not be specified in theobject tree. For instance, the snapshot image may accurately illustratethe visual appearance of resource including actual display sizes of HTMLelements and style information rendered by JAVASCRIPT.

In some implementations, extracting color content characteristic may bedone by extracting dominant colors of a portion of the snapshot imagecorresponding to the second node. In some implementations, dominantcolor can be extracted using a clustering technique such as k-meansclustering. For instance, each pixel of the portion of the snapshotimage corresponding to the second node may be treated as an independentcolor measurement (e.g., an independent k-means observation). The colorof each pixel may be represented using RGB color values ranging fromzero saturation (e.g., 0) to complete saturation (e.g., 255) for eachprimary color of light (e.g., red, green, and blue). A set of predefinedcolors (e.g., RGB(0, 0, 0), RGB(225, 0, 0), RGB(0, 255, 0), RGB(0, 0,225), RGB(255, 255, 0), RGB(255, 0, 255), RGB(0, 255, 255), RGB(255,255, 255), etc.) may be used as initial cluster means and each pixel maybe assigned to the cluster with the mean value closest to the RGB colorvalue of the pixel.

For instance, the RGB color value of each pixel may be compared witheach cluster mean using the following formula:|R_(mean)−R_(pixel)|+|G_(mean)−G_(pixel)|+|B_(mean)−B_(pixel)|=difference.In some implementations, a new mean may be created if the differencebetween the RGB color value for a pixel and the closest cluster meanexceeds a threshold value (e.g.|R_(mean)−R_(pixel)|+|G_(mean)−G_(pixel)|+|B_(mean)−B_(pixel)|>threshold).After assigning each pixel to the closest cluster (e.g., the clusterhaving a mean value closest to the color value for the pixel), each meancluster value may be re-computed based on the RGB color values of thepixels in each cluster. In some implementations, successive iterationsmay be performed by reassigning pixels to the closest cluster until theclusters converge on steady mean values or until a threshold number ofiterations has been performed.

Refined color clusters may be ranked based on the number of pixels ineach cluster. For instance, the color cluster with the most pixels maybe ranked as expressing the most dominant color, the color cluster withthe second most pixels may be ranked as expressing the second mostdominant color, etc. In some implementations, a weight to each color maybe assigned based on the number of pixels in the corresponding colorcluster relative to the total number of pixels in the snapshot image. Alist of extracted colors (e.g., RGB values) may be generated along witha weight or dominance ranking of each color.

Advantageously, k-means clustering may provide a color extractiontechnique which does not increase in time complexity as a function ofthe square of the number of pixels in the snapshot image (e.g.,time_complexity≠K*n² _(pixels)). Instead, k-means clustering has a timecomplexity proportional to the number of pixels multiplied by the numberof clustering iterations (e.g. time_complexity=K*n_(pixels)*iterations).The linear relationship between pixel number and time complexity withk-means clustering may result in an improved computation time over othercolor extraction techniques, especially when extracting colors fromrelatively large snapshot images.

In addition to extracting colors, color schemes may also be extracted byselecting different extracted colors as background color, text color,link color, button color, headline color, description color, button textcolor, or other portions of the third-party content item. For instance,the most dominant color (e.g., heaviest weighted, highest dominanceranking, etc.) may be selected as the background color for the contentitem. The extracted color with the highest multiplied saturation andweight (e.g., max(saturation*weight)) may be selected as the buttoncolor for the content item. The colors with the highest contrast and/orbrightness differences with the selected background color may beselected as the colors for the headline and description text. The morenoticeable color as the headline color is selected if more than twocolors are available.

As shown in FIG. 2, the method further includes associating the contentcharacteristic with the first node of the object tree (step 260). In oneimplementation, the memory location of the first node of the object tree(step 260) may now include the associated content characteristics orinclude memory references to the associated characteristics. In someimplementations, DOM node attributes may be set, toggled, oroverwritten. In some implementations, a list of changes to the firstnode may be kept, where the list references the first node.

As shown in FIG. 2, the method includes storing in a data structuremaintained in a memory element, the association of the determined firstnode and the associated content characteristic (step 270). The memoryelement may be part of the content item modification system 110, contentitem selection system 108, third-party content server 102, or datastorage devices 112. In some implementations, the data structure mayalso store the URL of the content item, account information related tothe resource or the third-party content item, and other information. Thedata structure may also store the object tree and which content slot themodifications are associated with. In some implementations, a list ofchanges to the first node may be used to update the data structure.After storing the content characteristics, when the content itemselection system 108 selects a third-party content item to be providedto a user device 106, the provided third-party content item is modifiedby the stored content characteristics.

FIG. 3 is a flowchart of one implementation of a process for extractingcontent characteristic for content item modification using content slotdimensions. The method 300 includes receiving a URL (step 310),rendering the resource to produce an object tree (step 320), determininga first node of the object tree representing a content slot, the firstnode having dimensions (step 330), and identifying a second node of theobject tree with equal dimensions as the first node (step 340). Themethod further includes extracting a content characteristic from thesecond node (step 350), associating the content characteristic with thefirst node of the object tree (step 360), and storing in a datastructure maintained in a memory element (step 370), the association ofthe determined first node and the associated content characteristic(step 380). In other implementations, these steps can be performed in adifferent order.

Most of the steps of the method 300 are similar to the correspondingsteps described in relation to FIG. 2. Specifically, receiving a URLfrom a content provider (step 310) corresponds to step 210). Renderingthe landing resource (step 320) corresponds to step 220. Extracting thecontent characteristic (step 350) corresponds to step 250. Associatingthe content characteristic (step 360) corresponds to step 260. Storingthe association (step 370) corresponds to step 270.

The method 300 includes determining a first node of the object treerepresenting a content slot, the first node having dimensions (step330). In some implementations, an object tree representing a receivedresource is traversed from the beginning. In some implementations, thefirst content slot that has a content characteristic specifyingdimensions is selected as the first node. In other implementations, athird-party content item that has dimensions is selected by the contentitem selection system 108. During the traversal, the first node isselected that has the same dimensions as the third-party content item.In some implementations, the entire object tree is traversed to identityall or some content slots that have the same dimensions as thethird-party content item. For instance, a resource may have multiplecontent slots having dimensions of 728×90 pixels. The resource may alsohave multiple content slots having dimensions of 180×150 pixels. Theselected third-party content item may have dimensions of 180×150 pixels.When traversing the object tree, all content slots with dimensions180×150 pixels may be identified, and one of these content slots may beselected as the first node. One of the plurality of content slots ischosen as a first node based on, for instance, whether a content slothas or does not have certain content characteristics. In someimplementations, one of the plurality of content slots may be chosenbased on total number of content characteristics it lacks or has.

The method 300 further includes identifying a second node of the objecttree with equal dimensions as the first node, the second node havingcontent characteristic (step 340). The identified second node has thesame dimensions as the first node. In some implementations, theidentified second node also has the same dimensions as the selectedthird-party content item. In some implementations, the object tree istraversed from the first node until a second node representing a contentslot having equal dimensions as the first node is encountered. Forinstance, referring briefly to FIG. 5, the first node 510 specifiesdimensions of 180×150 pixels and a second node is selected if it has thesame dimensions. The object tree may be traversed after the first node510, and a content slot 520 with dimensions of 336×280 pixels may beencountered which is not chosen due to having different dimensions.Further traversing the object tree, a content slot 530 with dimensionsof 180×150 pixels is encountered, which is then designated as the secondnode. In some implementations, a plurality of second nodes are selected,each of the plurality of second nodes specifying the same dimensions asthe first node. For instance, if the first node is identified to havedimensions of 180×150 pixels, then every content slot on the resourcewith the dimensions of 180×150 pixels is selected as one of theplurality of second nodes. In some implementations, a plurality ofcontent slots each with equal dimensions as the first node isidentified. In some implementations, a plurality of content slots eachwith equal dimensions as the first node within a predetermined distancefrom the first node is identified. One of the plurality of content slotsis selected as the second node. For instance, of the plurality ofcontent slots, the closest one to the first node may be selected as thesecond node. Distance may be measured in the number of connections orlink using the object tree, or in spatial distance using the snapshotimage. As another instance, of the plurality of content slots, the onewith the most or least number of content characteristics may be selectedas the second node. In some implementations, the plurality of contentslots is selected as a plurality of seconds nodes, as discussed below inrelation to FIG. 4.

FIG. 4 is a block diagram illustrating one implementations of thecontent item modification system 110 of FIG. 1 in greater detail,showing a receiver, a renderer module, a first node identifier module, asecond node identifier module, an extractor engine module, a linkermodule, a data manager module, and a node dimensions module. Contentitem modification system 110 is shown to include a receiver 402 and aprocessing circuit 404. Receiver 402 may be a communication interfacethat includes wired or wireless interfaces (e.g., jacks, antennas,transmitters, receivers, transceivers, wire terminals, Ethernet ports,WiFi transceivers, etc.) for conducting data communications with localor remote devices or systems. For instance, communications interface 402may allow content item modification system 110 to communicate withcontent item selection system 108, resource servers 104, user devices106, third-party content servers 102, data storage devices 112, andother components of computer system 100.

Processing circuit 404 is shown to include a processor 406 and memory408. Processor 406 may be implemented as a general purpose processor, anapplication specific integrated circuit (ASIC), one or more fieldprogrammable gate arrays (FPGAs), a CPU, a GPU, a group of processingcomponents, or other suitable electronic processing components.

Memory 408 may include one or more devices (e.g., RAM, ROM, flashmemory, hard disk storage, etc.) for storing data and/or computer codefor completing and/or facilitating the various processes, layers, andmodules described in the present disclosure. Memory 408 may includevolatile memory or non-volatile memory. Memory 408 may include databasecomponents, object code components, script components, or any other typeof information structure for supporting the various activities andinformation structures described in the present disclosure. In someimplementations, memory 408 is communicably connected to processor 406via processing circuit 404 and includes computer code (e.g., datamodules stored in memory 408) for executing one or more processesdescribed herein. In brief overview, memory 408 is shown to include arenderer module 410, a first node identifier module 412, a second nodeidentifier module 414, an extractor module 416, a linker module 418, adata manager module 420, and an optional node dimensions module 422.

Still referring to FIG. 4, memory 408 is shown to include a renderermodule 410. In some implementations, resource rendering is performed byrenderer module 410 rather than an external resource rendering service(e.g., resource renderer 111). Renderer module 410 may include thefunctionality of resource renderer 111 as described with reference toFIG. 1. For instance, renderer module 410 may be capable of interpretingresources from resource servers 104 and creating a visual representation(e.g., an image, a display, etc.) thereof.

Renderer module 410 may identify a particular resource using a URL orother indicator provided by content item modification system 110 as partof a request to modify content items. Renderer module 410 may read andinterpret marked up content (e.g., HTML, XML, image URLs, etc.) andformatting information (e.g., CSS, XSL, etc.) from resources and renderresources(e.g., according to W3C standards). Renderer module 410 maycreate a snapshot image of resources and/or construct a DOM treerepresenting resources.

The snapshot image may be a visual representation of the identifiedresource. The snapshot image may illustrate the visual appearance of theresource as presented on a user interface device (e.g., an electronicdisplay screen, a computer monitor, a touch-sensitive display, etc.)after rendering resource. The snapshot image may include content itemsin content slots, the content items comprising content characteristicsincluding color, style, font, animation, etc. In some implementations,the snapshot image may be a picture file having any viable fileextension (e.g. jpg, .png, .bmp, etc.).

The DOM tree may be a hierarchical model of a resource. Nodes in thedome tree may be specified as content slots. Nodes may further bespecified to have attributes or content characteristics such as fontinformation (e.g., font names, sizes, effects, etc.), color information(e.g., RGB color values, hexadecimal color codes, etc.), styles,dimensions, whether to play animations, sounds, or videos, and othercontent characteristics. The snapshot image and/or DOM tree may containcontent slot information as well as content characteristic associatedwith the content slot. Renderer module 410 may store the snapshot imageand/or DOM tree in memory 408 for subsequent use by other modulescontent item modification system 110.

Still referring to FIG. 4, memory 408 is shown to include a first nodeidentifier module 412. The first node identifier module 412 can beconnected to the renderer module 410 to receive the object tree or thesnapshot image or the memory location in which the object tree or thesnapshot image is stored. Generally, the first node identifier module412 may perform the stage (step 230) in FIG. 2. Specifically, the firstnode identifier module 412 may parse the DOM tree to determine a node ofthe DOM tree that corresponds to a content slot where third-partycontent items may be displayed. For instance, the first node identifiermodule 412 may search for particular words, tags, or attributions in theDOM tree to identify content slots. In some implementations, the firstnode identifier module 412 may include a tree traversal module thattraverses the DOM tree until a first node representing a content slot isencountered. In some implementations, the tree traversal module maytraverse the entire DOM tree to identify a plurality of nodes, and thefirst node identifier module 412 may select a first node from theplurality of nodes that has fewer content characteristics. In someimplementations, the first node identifier module 412 may choose one ofthe plurality of nodes based on total number of content characteristicsit lacks or has.

Still referring to FIG. 4, memory 408 is shown to include a second nodeidentifier module 414. The second node identifier module 414 can beconnected to the renderer module 410 or to the first node identifiermodule 412 to receive the object tree or the snapshot image or thememory location in which the object tree or the snapshot image isstored. The second node identifier module 414 may also receiveinformation from the first node identifier module 412 indicating whichcontent slot in the resource is the first node. Generally, the secondnode identifier module 414 may perform the stage (step 240) in FIG. 2.Specifically, the second node identifier module 414 identifies a secondnode of the object tree proximate to the first node, the second nodehaving a content characteristic (step 240). The second node may have oneor more content characteristic that is absent or is different from thefirst node. A content slot may specify a color, a color scheme, a font,styles, dimensions, content characteristic specifying that noanimations, sounds, or videos should be played, or other contentcharacteristic. In some implementations, the second node identifiermodule 414 may include a closest node selector that identifies a secondnode that is closest to the first node. A node distance calculator maycalculate the distance, which may be calculated by analyzing the objecttree to determine the number of connections or links between two nodesin the object tree. In some implementations, after the whole object treeis parsed and every content slot is found, the node distance calculatorcalculates the distance between the first node and some or all othercontent slots. The content slot with the smallest distance is selectedas the second node. In some implementations, spatial distance betweentwo nodes may be calculated by using the snapshot image produced by therenderer module 410 or the resource renderer 111.

In some implementations, the second node identifier module 414 includesa multi-node identifier that identifies a plurality of second nodes, asdescribed in relation to FIG. 4. Specifically, the multi-node identifiermay identify a plurality of second nodes within a predetermined distancefrom the first node.

In some implementations, the memory 408 may also include a contentcharacteristic analyzer that identifies a content characteristicassociated with at least some of the plurality of second nodes asdetermined by the multi-node identifier. The content characteristicanalyzer may include a node counter that determines a number of nodesrequired to be a majority in the plurality of second nodes, and thecontent characteristic analyzer may identify a content characteristicassociated with a majority of the plurality of second nodes. The contentcharacteristic analyzer may also include a content characteristicsmoother which averages the value of content characteristic associatedwith at least some of the plurality of second nodes. The contentcharacteristic analyzer may also include a font identifier thatidentifies a font associated with at least one of the plurality ofsecond nodes. The content characteristic analyzer may also include acontent characteristic compounder that assigns a weight to each of theplurality of second nodes and identifies a content characteristiccomprising a weighted average of the value of a content characteristicassociated with at least some of the plurality of second nodes.

Still referring to FIG. 4, memory 408 is shown to include an extractorengine module 416. The extractor engine module 416 can be connected tothe second node identifier module 414 and receive the second node or thememory location of the second node. The extractor engine module 416 mayalso receive the object tree, the snapshot image, or the resource or thememory location of the object tree, the snapshot image, or the resourcefrom the renderer module 410, the second node identifier module 414 orfrom the receiver 402. Generally, the extractor engine module 416 mayperform the stage (step 250) in FIG. 2. Specifically, extractor enginemodule 416 extracts a content characteristic from the second node. Thesecond node may have one or more content characteristic. The contentcharacteristics may be extracted from the object tree or the resource.In some implementations, the content characteristics may be extractedfrom a snapshot image of the resource that is rendered by the resourcerenderer 111 or the renderer module 410. In some implementations, onlyportions of the resource that correspond to the second node may berendered. Different content characteristics may be extracted from therendered image. Extracting from the rendered snapshot image allowsextraction of additional content characteristic that may not bespecified in the object tree. The extractor engine module 416 may alsoextract the dominant color or colors of the content item using aclustering technique such as k-means clustering.

Still referring to FIG. 4, memory 408 is shown to include a linkermodule 418. The linker module 418 is connected to the first nodeidentifier module 412 to receive the first node or the memory locationof the first node. The linker module 418 is also connected to theextractor engine module 416 to receive the extracted contentcharacteristic or memory location of the extracted contentcharacteristic. The linker module 418 may also receive the memorylocation of the object tree. Generally, the linker module 418 mayperform the stage (step 260) in FIG. 2. In one implementation, thelinker module 418 stores the extracted content characteristics or memoryreferences to the extracted content characteristics in the memorylocation of the first node of the object tree. In some implementations,the linker module 418 may set, toggle, or overwrite DOM node attributes.In some implementations, the linker module 418 may create a list ofchanges that references the first node.

Still referring to FIG. 4, memory 408 is shown to include a data managermodule 420. The data manager module 420 can be connected to the linkermodule 418 and may receive the linker first node. Generally, the datamanager module 420 may perform the stage (step 270) in FIG. 2.Specifically, the data manager module 420 may create or update a datastructure that stores the first node with the extract contentcharacteristic. In some implementations, the data structure may alsostore the URL of the content item, account information related to theresource or the third-party content item, and other information. Thedata structure may also store the object tree and which content slot themodifications are associated with. In some implementations, a list ofchanges to the first node may be used to update the data structure.

Still referring to FIG. 4, memory 408 is shown to optionally includenode dimensions module 422. The node dimension module 422 may beconnected to the first node identifier module 412, and the second nodeidentifier module 414. The node dimension module 422 may also receivethe object tree or the memory location of the object tree. The nodedimension module 422 may determine the node dimensions of a given nodein the object tree. The first node identifier 412 and the second nodeidentifier 414 may use the node dimension module 422 to perform thestages (step 330) and (step 340) in FIG. 3. Alternatively, the nodedimension module 422 may perform these stages. In some implementations,the node dimension module 422 determines a first node of the object treerepresenting a content slot to have dimensions. In some implementations,the node dimension module 422 traverses the object tree from thebeginning. In some implementations, the node dimension module 422selects the first content slot that has a content characteristicspecifying dimensions as the first node. In other implementations, thenode dimension module 422 accesses dimensions received by the receiver402. The dimensions may be, for instance, of a third-party content itemselected by the content item selection system 108. During the traversal,the node dimension module 422 selects the first node that has the samedimensions as the received dimensions. In some implementations, the nodedimension module 422 traverses the entire object tree to identity all orsome content slots that have the same dimensions as the receiveddimensions. The node dimension module 422 may also identify a secondnode of the object tree with equal dimensions as the first node, thesecond node having content characteristic. In some implementations, thenode dimension module 422 identifies a second node that has the samedimensions as the first node or the third-party content item. In someimplementations, the node dimension module 422 selects a plurality ofsecond nodes, each node specifying the same dimensions as the firstnode.

Implementations of the subject matter and the operations described inthis specification may be implemented in digital electronic circuitry,or in computer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Implementations of the subjectmatter described in this specification may be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on one or more computer storage medium forexecution by, or to control the operation of, data processing apparatus.Alternatively or in addition, the program instructions may be encoded onan artificially-generated propagated signal (e.g., a machine-generatedelectrical, optical, or electromagnetic signal) that is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium maybe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal, a computerstorage medium may be a source or destination of computer programinstructions encoded in an artificially-generated propagated signal. Thecomputer storage medium may also be, or be included in, one or moreseparate components or media (e.g., multiple CDs, disks, or otherstorage devices). Accordingly, the computer storage medium is bothtangible and non-transitory.

The operations described in this disclosure may be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources.

The term “client or “server” include all kinds of apparatus, devices,and machines for processing data, including a programmable processor, acomputer, a system on a chip, or multiple ones, or combinations, of theforegoing. The apparatus may include special purpose logic circuitry,e.g., a field programmable gate array (FPGA) or an application-specificintegrated circuit (ASIC). The apparatus may also include, in additionto hardware, code that creates an execution environment for the computerprogram in question (e.g., code that constitutes processor firmware, aprotocol stack, a database management system, an operating system, across-platform runtime environment, a virtual machine, or a combinationof one or more of them). The apparatus and execution environment mayrealize various different computing model infrastructures, such as webservices, distributed computing and grid computing infrastructures.

The systems and methods of the present disclosure may be completed byany computer program. A computer program (also known as a program,software, software application, script, or code) may be written in anyform of programming language, including compiled or interpretedlanguages, declarative or procedural languages, and it may be deployedin any form, including as a stand-alone program or as a module,component, subroutine, object, or other unit suitable for use in acomputing environment. A computer program may, but need not, correspondto a file in a file system. A program may be stored in a portion of afile that holds other programs or data (e.g., one or more scripts storedin a markup language document), in a single file dedicated to theprogram in question, or in multiple coordinated files (e.g., files thatstore one or more modules, sub-programs, or portions of code). Acomputer program may be deployed to be executed on one computer or onmultiple computers that are located at one site or distributed acrossmultiple sites and interconnected by a communication network.

The processes and logic flows described in this specification may beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows may also be performedby, and apparatus may also be implemented as, special purpose logiccircuitry (e.g., an FPGA or an ASIC).

Processors suitable for the execution of a computer program include bothgeneral and special purpose microprocessors, and any one or moreprocessors of any kind of digital computer. Generally, a processor willreceive instructions and data from a read-only memory or a random accessmemory or both. The essential elements of a computer are a processor forperforming actions in accordance with instructions and one or morememory devices for storing instructions and data. Generally, a computerwill also include, or be operatively coupled to receive data from ortransfer data to, or both, one or more mass storage devices for storingdata (e.g., magnetic, magneto-optical disks, or optical disks). However,a computer need not have such devices. Moreover, a computer may beembedded in another device (e.g., a mobile telephone, a personal digitalassistant (PDA), a mobile audio or video player, a game console, aGlobal Positioning System (GPS) receiver, or a portable storage device(e.g., a universal serial bus (USB) flash drive), etc.). Devicessuitable for storing computer program instructions and data include allforms of non-volatile memory, media and memory devices semiconductormemory devices (e.g., EPROM, EEPROM, and flash memory devices; magneticdisks, e.g., internal hard disks or removable disks; magneto-opticaldisks; and CD-ROM and DVD-ROM disks). The processor and the memory maybe supplemented by, or incorporated in, special purpose logic circuitry.

To provide for interaction with a user, implementations of the subjectmatter described in this specification may be implemented on a computerhaving a display device (e.g., a CRT (cathode ray tube), LCD (liquidcrystal display), OLED (organic light emitting diode), TFT (thin-filmtransistor), or other flexible configuration, or any other monitor fordisplaying information to the user and a keyboard, a pointing device,e.g., a mouse, trackball, etc., or a touch screen, touch pad, etc.) bywhich the user may provide input to the computer. Other kinds of devicesmay be used to provide for interaction with a user as well; forinstance, feedback provided to the user may be any form of sensoryfeedback (e.g., visual feedback, auditory feedback, or tactilefeedback), and input from the user may be received in any form,including acoustic, speech, or tactile input. In addition, a computermay interact with a user by sending documents to and receiving documentsfrom a device that is used by the user; for instance, by sending webpages to a web browser on a user's client device in response to requestsreceived from the web browser.

Implementations of the subject matter described in this disclosure maybe implemented in a computing system that includes a back-end component(e.g., as a data server), or that includes a middleware component (e.g.,an application server), or that includes a front-end component (e.g., aclient computer) having a graphical user interface or a web browserthrough which a user may interact with an implementation of the subjectmatter described in this disclosure, or any combination of one or moresuch back-end, middleware, or front-end components. The components ofthe system may be interconnected by any form or medium of digital datacommunication (e.g., a communication network). Communication networksinclude a LAN and a WAN, an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anydisclosures or of what may be claimed, but rather as descriptions offeatures specific to particular implementations of particulardisclosures. Certain features that are described in this disclosure inthe context of separate implementations may also be implemented incombination in a single implementation. Conversely, various featuresthat are described in the context of a single implementation may also beimplemented in multiple implementations separately or in any suitablesubcombination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination may in some cases be excisedfrom the combination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the implementations described above should not beunderstood as requiring such separation in all implementations, and itshould be understood that the described program components and systemsmay generally be integrated together in a single software product orpackaged into multiple software products embodied on one or moretangible media.

Thus, particular implementations of the subject matter have beendescribed. Other implementations are within the scope of the followingclaims. In some cases, the actions recited in the claims can beperformed in a different order and still achieve desirable results. Inaddition, the methods depicted in the accompanying figures do notnecessarily require the particular order shown, or sequential order, toachieve desirable results. In certain implementations, multitasking andparallel processing may be advantageous.

1. A computerized method for automatically creating a contentmodification scheme for content, the method comprising: receiving auniform resource locator (URL) from a content provider, the URLidentifying a resource; rendering the resource to produce an objecttree; determining a first node of the object tree representing a contentslot; identifying a second node of the object tree proximate to thefirst node, the second node having a content characteristic; extractingthe content characteristic from the second node; associating the contentcharacteristic with the first node of the object tree; and storing, in adata structure maintained in a memory element, the association of thedetermined first node and the associated content characteristic.
 2. Themethod of claim 1, wherein: determining a first node of the object treecomprises traversing the object tree until a first node representing acontent slot is encountered.
 3. The method of claim 1, whereindetermining a first node of the object tree comprises traversing theentire object tree to identify a plurality of nodes representing acontent slot and selecting one of the plurality of nodes.
 4. The methodof claim 1, wherein identifying a second node comprises identifying asecond node immediately adjacent in the object tree to the first node.5. The method of claim 1, wherein identifying a second node comprisesidentifying a plurality of nodes within a predetermined distance fromthe first node.
 6. The method of claim 5, further comprising identifyinga content characteristic associated with at least some of the pluralityof second nodes.
 6. The method of claim 6, wherein identifying a contentcharacteristic comprises identifying a content characteristic associatedwith a majority of the plurality of second nodes.
 8. The method of claim6, wherein identifying a content characteristic comprises averaging thevalue of a content characteristic associated with at least some of theplurality of second nodes.
 9. The method of claim 6, wherein identifyinga content characteristic comprises identifying a font associated with atleast one of the plurality of second nodes.
 10. The method of claim 6,wherein identifying a content characteristic comprises assigning aweight to each of the plurality of second nodes and identifying acontent characteristic comprising a weighted average of the value of acontent characteristic associated with at least some of the plurality ofsecond nodes.
 11. An apparatus for automatically creating a contentmodification scheme for content, comprising: a receiver accepting a URLfrom a content provider, the URL identifying a resource; a renderer incommunication with the receiver, the renderer producing an object treeassociated with the resource; a first node identifier accessing theobject tree produced by the renderer, the first node identifierdetermining a first node of the object tree representing a content slot;a second node identifier in communication with the first nodeidentifier, the second node identifier determining a second node of theobject tree proximate to the first node, the second node having acontent characteristic; an extractor engine in communication with thesecond node identifier, the extractor engine extracting contentcharacteristics of the second node; a linker in communication with theextractor engine and the first node identifier, the linker associatingthe content characteristic with the first node of the object tree; and adata manager in communication with the linker and a memory element, thedata manager storing the association of the determined first node andthe associated content characteristic in a data structure maintained inthe memory element.
 12. The apparatus of claim 11, wherein the firstnode identifier comprises a tree traversal module accessing the objecttree produced by the renderer, the tree traversal module traversing theobject tree until a first node representing a content slot isencountered.
 13. The apparatus of claim 11, wherein the first nodeidentifier comprises: a tree traversal module accessing the object treeproduced by the renderer, the tree traversal module traversing theentire object tree to identify a plurality of nodes representing acontent slot; and a node selector in communication with the treetraversal module, the node selector selecting one of the plurality ofnodes to determine a first node.
 14. The apparatus of claim 11, whereinthe second node identifier comprises a closest node selector incommunication with the first node identifier, the closest node selectoridentifying the second node immediately adjacent in the object tree tothe first node.
 15. The apparatus of claim 11, wherein the second nodeidentifier comprises: a node distance calculator in communication withthe first node identifier, the node distance calculator calculating adistance between the first node and each of a plurality of second nodesin the object tree; and a multi-node identifier in communication withthe renderer, the multi-node identifier identifying the plurality ofsecond nodes within a predetermined distance from the first node. 16.The apparatus of claim 15, further comprising a content characteristicanalyzer in communication with the multi-node identifier, the contentcharacteristic analyzer identifying a content characteristic associatedwith at least some of the plurality of second nodes.
 17. The apparatusof claim 16, wherein the content characteristic analyzer furthercomprises a node counter accessing the object tree produced by therenderer, the node counter determining a number equal to a minimumnumber of nodes required to be a majority of the plurality of secondnodes; and wherein a content characteristic analyzer, in communicationwith the node counter, identifies a content characteristic associatedwith at least the number of nodes.
 18. The apparatus of claim 16,wherein the content characteristic analyzer further comprises contentcharacteristic smoother in communication with the content characteristicanalyzer, the content characteristic smoother averaging the value of acontent characteristic associated with at least some of the plurality ofsecond nodes.
 19. The apparatus of claim 16, wherein the contentcharacteristic analyzer further comprises a font identifier incommunication with the content characteristic analyzer, the fontidentifier identifying a font associated with at least one of theplurality of second nodes.
 20. The apparatus of claim 16, wherein thecontent characteristic analyzer further comprises content characteristiccompounder in communication with the content characteristic analyzer,the content characteristic compounder: assigning a weight to each of theplurality of second nodes; and computing a weighted average of the valueof a content characteristic associated with at least some of theplurality of second nodes. 21-40. (canceled)